This disclosure relates generally to online content distribution, and more specifically to generating lists of candidate topics for recommendation to users of digital magazines in view of correlation between computer applications installed on user devices associated with the users of the digital magazines and known topics for the users.
Digital distribution channels disseminate to users a wide variety of digital content including videos, text, images, audio, links, and interactive media (e.g., games, collaborative content) from external or internal sources. A user of a digital magazine mobile application can enjoy different kinds of content (e.g., text articles, image files, audio files or video files) that are displayed on the digital magazine. Different users of digital magazines may have different preferences or personal interest and may expect to view content on the digital magazines that is more related to their own preferences. For example, one group of users of digital magazines may expect to view content of sports since they are sports lovers, and another group of users of digital magazines may expect to view content of newly released movies since these users are movie lovers. However, some existing solutions of digital magazines make different users to consume same or similar content instead of recommending personalized content that correspond to different users' preferences. Additionally, recommendation of content to different groups of users of digital magazines may not be accurate without considering and analyzing across a large user database of digital magazines. Such limitations degrade user experience with digital magazines.